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Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). enableHiveSupport().getOrCreate()

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

That resulted in server farms, collecting volumes of log data from customer interactions, data which was then aggregated and fed into machine learning algorithms which created data products as pre-computed results, which in turn made web apps smarter and enhanced e-commerce revenue. We keep feeding the monster data.

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Run Spark SQL on Amazon Athena Spark

AWS Big Data

For interactive applications, Athena Spark allows you to spend less time waiting and be more productive, with application startup time in under a second. Running SQL on data lakes is fast, and Athena provides an optimized, Trino- and Presto-compatible API that includes a powerful optimizer.

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Generate security insights from Amazon Security Lake data using Amazon OpenSearch Ingestion

AWS Big Data

Optionally, specify the Amazon S3 storage class for the data in Amazon Security Lake. For more information, refer to Lifecycle management in Security Lake. Review the details and create the data lake. Choose Next. Choose Component templates to verify the OCSF component templates.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. Historically, grad students in physics and physical sciences have been excellent candidates for data science teams. Or something.

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Periscope Data Expands to Israel, Empowering Data Teams with Powerful Tools

Sisense

He talked through how the mind-blowing escalation of data and the drastic reduction in the cost of its storage has led to more complex, sophisticated uses of data and a shift in the way it’s managed and consumed. He concluded that data teams can influence the transformation of startups into unicorns. A true unicorn.

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Q&A with Greg Rahn – The changing Data Warehouse market

Cloudera

And so I actually transitioned out of that group and into the Big Data Appliance group at Oracle, but soon realized that if that was what I wanted to keep doing, this up and coming company called Cloudera might be a better place to do it since these new technologies weren’t just a hobby at Cloudera. As you mentioned, Qlik is in there.